INTRODUCTION
Ultrasonographic anomalies and soft markers are common indications for prenatal chromosomal analysis.1 Standard karyotyping and chromosomal microarray (CMA) have become the primary diagnostic tools for fetuses with growth disorders and congenital anomalies. Recently, low-pass genome sequencing (low-pass GS) with enhanced resolution and high throughput has emerged as an alternative to CMA for genetic testing.2, 3 It has been applied to genetic diagnoses in prenatal, miscarriage, and postnatal cases,4-6 and was reported to have a 1.7%-3.4% improvement in additional yield compared with routine CMA.2, 6 Furthermore, low-pass GS has received attention due to its shorter turnaround time, reduced DNA requirements, lower technical repetition rate and lower cost.4
The yields of aneuploidy and likely pathogenic/pathogenic copy number variations (pCNV) vary with different ultrasonographic findings. Previous studies showed that the yield of pCNV was 6%-7% in ultrasonography anomalous fetuses with a normal karyotype,7, 8 and 0.4%-2% in fetuses without anomalies.9-11 Cardiovascular, genitourinary, skeletal, and central nervous system defects were reported to be most commonly associated with chromosomal aberrations.12-18Therefore, the American College of Obstetricians and Gynecologists (ACOG) and the Society for Maternal-Fetal Medicine (SMFM) recommend CMA as a first-tier test in the diagnostic evaluation of fetal structural abnormalities for fetuses undergoing prenatal diagnosis.19 Additionally, previous studies have demonstrated that aneuploidy and pCNV were frequently presented in specific soft markers, such as increased nuchal translucency, ventriculomegaly, and thickened nuchal fold.20-23 In particular, the SMFM recommends CMA for fetuses with ventriculomegaly.24 However, ultrasonographic anomalies and soft markers comprise diverse subtypes, which may have significant differences in the yield of aneuploidy and pCNV.25-27
Therefore, it is crucial to systematically explore the correlation between various ultrasonographic anomalies and soft markers and aneuploidy/ pCNV. In this study, we comprehensively analyzed the yield of aneuploidy and pCNV in 12 types of ultrasonographic anomalies and soft markers based on a large cohort of 43,721 fetuses to provide data support for the risk assessment of aneuploidy/pCNV underlying different ultrasonographic findings. For each aneuploidy/pCNV, we compared the ultrasonographic characteristics of fetuses with and without chromosomal aberrations to elucidate the association of specific genomic alterations with specific ultrasonographic anomalies.